At Nfq we research, collaborate and work with institutions and partners to add value to our clients and expand our capabilities.
We collaborate and sponsor projects and new initiatives to reinvent the Banking, Market and Insurance industries.
International PyData summit in Madrid
The first PyData event in Spain was held between 8 and 10 April in Madrid, specifically in the BBVA Innovation Centre and in the prestigious arena that is the Madrid Google Campus. This conference was organized by the Spanish Python Community, under NumFocus supervision, and served as a meeting point for users and developers of data analysis tools in Python language.
Nfq Collaborates with Carlos III and CDTI in supercomputing project
Jointly with the Carlos III University and the CDTI, we are developing a project to process data and information in a efficiently, distribute and in a faster way, based on the whole expertise regarding the supercomputing world.
Nfq collaborates with Universidad Politécnica of Madrid in its Smart Contracts project
As part of this collaboration, Nfq developed with Universidad Politécnica de Madrid, a Smart Contracts demo for the financial sector based on BlockChain technology.
The Kalman Filter is a time series estimation algorithm based on bayesian statistics. It is a powerful tool for combining information and dealing with uncertainty, and it is widely used to estimate unobservable or unreliable data.
Self-consisted correlated evolution model
An industrial simulation needs for a huge amount of data, interest rate curves, foreign exchange rates, volatility surfaces, stock market prices, and a consistent methodology to efficiently consider mutual influence among all of them, in the way of a correlation structure.
QDos. Our reputational risk management tool
The management of reputational risk is essential in the modern financial paradigm. And sentiment analysis is a powerful tool to analyse the reputation of certain financial institutions.
Nfq has evolved the original economic capital tool of one of the largest spanish retail bank, developed in Matlab, which ran once per year and spent 12 hours, to a Spark approach running every month and spending 40 minutes.
Improving the ETL process for ALM, which are acknowledged by being high demanded systems, since the processing and data storage viewpoint, transforming from a SAS architecture into a flexible Cloud one.
Machine Learning to measure reputational risk
The tool developed by nfqSolutions allows a financial institution to measure the reputational risk. An algorithm, once being trained by using machine learning techniques, catalogues the feeling of the Twitter entries related to the referred financial institution.
Following the path as we’ve started with Startup grind Asturias, we are collaborating with Astur Valley, keeping our compromise and support to the innovative initiatives.
Startup Grind Asturias
Since the beginning of Startup Grind Asturias, Nfq has been supporting, as the main sponsor, the movement that has been produced in Asturias, within the Startup’s sector.